H
Humberto González-Díaz
Researcher at University of the Basque Country
Publications - 213
Citations - 6465
Humberto González-Díaz is an academic researcher from University of the Basque Country. The author has contributed to research in topics: Quantitative structure–activity relationship & Complex network. The author has an hindex of 46, co-authored 207 publications receiving 6129 citations. Previous affiliations of Humberto González-Díaz include Central University of Las Villas & University of Valencia.
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Medicinal chemistry and bioinformatics--current trends in drugs discovery with networks topological indices.
TL;DR: The work described here, review and comment on the "quo vadis" and challenges in the definition of TIs as the authors enter the new century.
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Proteomics, networks and connectivity indices.
Humberto González-Díaz,Yenny González-Díaz,Lourdes Santana,Florencio M. Ubeira,Eugenio Uriarte +4 more
TL;DR: This work reviews and comment on the challenges and new trends in the definition and applications of CIs in Proteomics, and focuses on CIs to describe Protein Interaction Networks or RNA co‐expression networks.
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Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds.
Francisco J. Prado-Prado,Humberto González-Díaz,Octavio Martínez de la Vega,Florencio M. Ubeira,Kuo-Chen Chou +4 more
TL;DR: The development of an mt-QSAR for more than 500 drugs tested in the literature against different parasites and the outputs of the QSAR are used to construct, by the first time, a multi-species Complex Networks of antiparasite drugs.
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A QSAR model for in silico screening of MAO-A inhibitors. Prediction, synthesis, and biological assay of novel coumarins.
Lourdes Santana,Eugenio Uriarte,Humberto González-Díaz,Giuseppe Zagotto,Ramón Soto-Otero,Estefanía Méndez-Alvarez,Estefanía Méndez-Alvarez,Estefanía Méndez-Alvarez +7 more
TL;DR: This work explores the potential of the MARCH-INSIDE methodology to seek a QSAR for MAO-A inhibitors from a heterogeneous series of compounds and correctly predicted 13 compounds with only two mistakes on compounds with activities very close to the cutoff point established for the model.
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Computational tool for risk assessment of nanomaterials: novel QSTR-perturbation model for simultaneous prediction of ecotoxicity and cytotoxicity of uncoated and coated nanoparticles under multiple experimental conditions.
Valeria V. Kleandrova,Feng Luan,Feng Luan,Humberto González-Díaz,Humberto González-Díaz,Juan M. Ruso,Alejandro Speck-Planche,Alejandro Speck-Planche,M. Natália D. S. Cordeiro +8 more
TL;DR: A unified QSTR-perturbation model is developed to simultaneously probe ecotoxicity and cytotoxicity of NPs under different experimental conditions, including diverse measures of toxicities, multiple biological targets, compositions, sizes and conditions to measure those sizes, shapes, times during which the biological targets were exposed to NPs, and coating agents.